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Role of precious metals in global risk dynamics: Exploring their impact from a connectedness approach

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  • Oxley, Les
  • Hu, Yang
  • Corbet, Shaen
  • Goodell, John W.

Abstract

In this research, we investigate the dynamic relationship between global volatility, as measured by Common Volatility (COVOL), and major precious metals. Utilising the popular Time-Varying Parameter Vector Autoregression (TVP-VAR) model, we uncover distinctive and complex interconnectedness that respond sharply to key global events. Our findings indicate that COVOL typically acts as a volatility receiver from precious metals, revealing that global market volatility is significantly influenced by fluctuations in the precious metals market with pronounced spillover effects experienced during major economic, financial and geopolitical events, underscoring the intricate interplay between global volatility and precious metal values. This research not only deepens our understanding of the global financial landscape but also provides critical insights for policymakers and investors navigating these markets.

Suggested Citation

  • Oxley, Les & Hu, Yang & Corbet, Shaen & Goodell, John W., 2023. "Role of precious metals in global risk dynamics: Exploring their impact from a connectedness approach," Finance Research Letters, Elsevier, vol. 58(PD).
    • Handle: RePEc:eee:finlet:v:58:y:2023:i:pd:s1544612323008991
    DOI: 10.1016/j.frl.2023.104527
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    References listed on IDEAS

    as
    1. Lars Forsberg & Eric Ghysels, 2007. "Why Do Absolute Returns Predict Volatility So Well?," Journal of Financial Econometrics, Oxford University Press, vol. 5(1), pages 31-67.
    2. Koop, Gary & Pesaran, M. Hashem & Potter, Simon M., 1996. "Impulse response analysis in nonlinear multivariate models," Journal of Econometrics, Elsevier, vol. 74(1), pages 119-147, September.
    3. Figuerola-Ferretti, Isabel & McCrorie, J. Roderick, 2016. "The shine of precious metals around the global financial crisis," Journal of Empirical Finance, Elsevier, vol. 38(PB), pages 717-738.
    4. Pesaran, H. Hashem & Shin, Yongcheol, 1998. "Generalized impulse response analysis in linear multivariate models," Economics Letters, Elsevier, vol. 58(1), pages 17-29, January.
    5. Xu, Danyang & Hu, Yang & Corbet, Shaen & Goodell, John W., 2023. "Volatility connectedness between global COVOL and major international volatility indices," Finance Research Letters, Elsevier, vol. 56(C).
    6. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    7. Engle, Robert F. & Campos-Martins, Susana, 2023. "What are the events that shake our world? Measuring and hedging global COVOL," Journal of Financial Economics, Elsevier, vol. 147(1), pages 221-242.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    COVOL; Gold; Precious metals; Connectedness; COVID-19;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • E3 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles
    • F3 - International Economics - - International Finance

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